52 citations · 82 across the 13 of their papers we have counts for
10 papers · 1 filter
Hyper-RED: Scalable Event Pre-training via Semantic Hypergraph Distillation
Meisen Wang, Zhiqiang Tian, Wei Bao +3
Event cameras have shown great potential for robust visual perception, yet scaling event representation learning remains challenging due to the scarcity of large-scale annotated ev…
GeoTrace: Geometry-Aware Trajectory Token Compression for Video Large Language Models
Guohuan Xie, Mengqi Lei, Chuan Shi +3
Although Video Large Language Models (Video LLMs) have shown strong performance in video understanding, their efficiency is still limited by the large number of visual tokens. Exis…
M^2C-EvDet: Multi-Domain Multi-Order Cross-Modal Knowledge Distillation for Event-based Object Detection
Wei Bao, Siqi Li, Shouan Pan +2
Event-based object Detection (EvDet), as a biologically inspired visual perception paradigm, demonstrates superior performance in scenarios demanding high temporal resolution and a…
Count Anything
Mengqi Lei, Shuokun Cheng, Wei Bao +4
Object counting remains fragmented across domain-specific datasets and task formulations, despite rapid progress in generalist vision models. Existing counting models are often tai…
Hypergraph as Language
Mengqi Lei, Guohuan Xie, Shihui Ying +6
Large language models (LLMs) have recently shown strong potential in modeling relational structures. However, existing approaches remain fundamentally graph-centric: they focus on…
Hyper-FSAD: Training-Free and Language-Free Few-Shot Anomaly Detection via Sparse Hyper Matching
Guohuan Xie, Xin He, Dingying Fan +2
Few-shot anomaly detection (FSAD) is particularly valuable when only a few normal images are available in a new target domain, while anomalous cases are rare, diverse, and difficul…
Rethinking Event-Based Object Detection through Representation-Level Temporal Aggregation and Model-Level Hypergraph Reasoning
Meisen Wang, Hao Deng, Wei Bao +5
Event cameras provide microsecond-level temporal resolution, low latency, and high dynamic range, offering potential for perception under fast motion and challenging illumination c…
RACANet: Reliability-Aware Crowd Anchor Network for RGB-T Crowd Counting
Jinghao Shi, Mengqi Lei, Kunliang He +3
RGB-Thermal (T) crowd counting aims to integrate visible-spectrum and thermal infrared information to improve the robustness of crowd density estimation in complex scenes. Although…
Hyper-FEOD: Sparse Hypergraph-Enhanced Frame-Event Object Detection with Fine-Grained MoE
Wei Bao, Yuehan Wang, Tianhang Zhou +1
The integration of frame-based RGB cameras with event streams constitutes a promising paradigm for robust object detection under challenging dynamic conditions. Nevertheless, effec…
I3DM: Implicit 3D-aware Memory Retrieval and Injection for Consistent Video Scene Generation
Jia Li, Han Yan, Yihang Chen +6
Despite remarkable progress in video generation, maintaining long-term scene consistency upon revisiting previously explored areas remains challenging. Existing solutions rely eith…